Monday, 23 July 2012

As a clinician, health IT architect and computational model-builder, I’ve been focused for the past three decades on how to use health IT to transform data into information and information into knowledge, in a way that improve care value. I’ve come to realize that highly effective and efficient care delivery (including prevention, assessment of risk, and the diagnosis oand treatment of health problems) depends on useful, valid clinical knowledge providing evidence-based decision support.

This knowledge can help continually improve care outcomes though methods and tools such as patient-centeredcognitive support, computerized clinical decision systems, and evidence-based clinical practice guidelines/pathways. These things are necessary if we want bridge the knowledgegap.
In any case, gaining this crucial knowledge depends on creating, continually evolving and disseminating useful, actionable, valid information and presenting it in a way that avoids overloading theclinician and patient.

And generating such valuable information requires adequate amounts and diversities of valid and reliable data. Some of these requisite data can come from today’s "Big Data" stores, which are typically insurance claims (administrative) data. While such claims data have usefulness, they are grossly inadequate when it comes to creating the kinds of information and emerging the kinds of clinical knowledge necessary to improve care quality and cost in any truly meaningful way.